Bring speed and efficiency to your data interactions

Tiger DataSphere can help you better manage your data ecosystem

Arrow
Transforming data management to make way for better efficiency

Every enterprise wants to bring significant speed, efficiency, and accuracy to how they interact and work with data. As breakthrough technologies emerge, organizations can benefit tremendously from engineering these advancements into their data systems, processes, and products.

Tiger Analytics DataSphere, a set of accelerators and frameworks, enables engineering teams to build and manage data ecosystems with significant agility and speed. Furthermore, it supports enterprises towards better data awareness and trust.

The Tiger DataSphere enables four key areas:

  • Establish a modern data foundation
  • Optimize cloud data and analytics platforms
  • Democratize data across the enterprise
  • Build intelligent data platforms

These tools cut across legacy technologies and new-age cloud platforms like AWS, Azure, GCP, Databricks, and Snowflake, to name a few.

Every enterprise wants to bring significant speed, efficiency, and accuracy to how they interact and work with data. As breakthrough technologies emerge, organizations can benefit tremendously from engineering these advancements into their data systems, processes, and products.

Tiger Analytics DataSphere, a set of accelerators and frameworks, enables engineering teams to build and manage data ecosystems with significant agility and speed. Furthermore, it supports enterprises towards better data awareness and trust.

The Tiger DataSphere enables four key areas:

  • Establish a modern data foundation
  • Optimize cloud data and analytics platforms
  • Democratize data across the enterprise
  • Build intelligent data platforms

These tools cut across legacy technologies and new-age cloud platforms like AWS, Azure, GCP, Databricks, and Snowflake, to name a few.

Tiger DataSphere features

Code generation and automation workbench
Utilities to automate code generation by taking user inputs as metadata or workflows in self-service templates. Covers various areas like ETL, Data Modelling, and Reporting. Gen AI-powered modules like self-service chatbots, code generation, and synthetic data generation.
Read More
Infrastructure automation
A DataOps toolkit for infrastructure automation and management. Automate infrastructure provisioning and management using IaaC tools across cloud platforms.
Read More
A UI-driven approach to managing data
A self-service, low/no-code data management platform that facilitates seamless data integration, efficient data ingestion, robust data quality checks, data standardization, and effective data provisioning. Its user-centric, UI-driven approach enables professionals with diverse technical proficiencies to manage their data resources effortlessly.
Read More
Understand your data and ML health
Set of tools, patterns, and practices to build Data observability components for data workloads across cloud platforms. Provides continuous monitoring and alerting of potential issues across the business value chain. ML-driven anomaly detection and next best action. Covers data, pipelines, infra, business, and model metrics.
Read More
Monitoring performance bottlenecks and cost
Tiger DataSphere has two accelerators:
Performance bottlenecks: A no-code, self-service accelerator to help report creators to review performance bottlenecks in their reporting ecosystem (PowerBI & Tableau).
Cost monitoring: A FinOps governance solution to optimize spending on cloud resources. It monitors jobs, clusters, and other components, identifying hotspots and alerting relevant stakeholders.

Read More
Democratize your data assets
Tiger’s Data Catalog enables end-to-end data discovery across all your data assets – from databases to BI reports. No-code self-service accelerators can be used in a standalone manner to extract metadata from BI assets.
This solution supports all metadata, provides end-to-end lineage, and can be integrated with external tools.

Read More
Our ways of working
Building intelligent data platforms
Our ways of working

We continuously evolve and refine platform architectures and workflows for various business use cases. These architectures have been customized to major cloud platforms, have easy-to-assemble modules and libraries, and are built using best-in-class engineering protocols.

Using our foundational architecture and utilities, we have pre-built the following platforms.

Customer JIA
This is our customer journey, intelligence, and activation platform. It enables hyper-personalized customer journeys and next-best actions on a cloud-native architecture. It provides a unified data fabric covering multiple industry domains. It comes with a pre-built suite of customer intelligence models.
Supply Chain AI
This cloud-native platform ingests data from across your supply chain partners and provides a centralized, real-time view of your global supply chain. Its predictive and prescriptive analytics capabilities help with real-time decision-making.
MarketingIQ
This cloud-native marketing analytics platform ingests data from a multitude of first, second, and third-party data. It has pre-build modules for use cases across the customer lifecycle – lead identification, segmentation, media channel optimization, media mix measurement, customer engagement, and CLTV.

Why choose us?

Accelerated time to value with the pre-built foundational components
Leverage custom and open-source components for easy integration with Cloud PaaS services
Open-IP accelerators available to our clients at no cost
Significant effort/cost savings in platform setup and governance
Copyright © 2024 Tiger Analytics | All Rights Reserved